KLA vs Fiddler
Fiddler is strong for AI observability, monitoring, and guardrails programs. KLA focuses on workflow decision governance (checkpoints + queues) and verifiable evidence exports.
Tracing is necessary. Regulated audits usually ask for decision governance + proof: enforceable policy gates and approvals, packaged as a verifiable evidence bundle (not just raw logs).
For ML platform, compliance, risk, and product teams shipping agentic workflows into regulated environments.
Ultimo aggiornamento: 17 dic 2025 · Versione v1.0 · Non costituisce consulenza legale.
A chi è rivolta questa pagina
Un inquadramento dal punto di vista dell'acquirente (non una denigrazione).
For ML platform, compliance, risk, and product teams shipping agentic workflows into regulated environments.
A cosa serve realmente Fiddler
Basato sulla sua funzione principale (e dove si sovrappone).
Fiddler is built for AI observability and monitoring: tracking performance, risk signals, and guardrail outcomes across AI systems. It is a strong fit when your program starts with measurement and reporting.
Sovrapposizione
- Both can support risk/quality measurement programs and ongoing monitoring signals.
- Both can support "prove it" conversations. The difference is whether proof is packaged from workflow decisions or assembled from monitoring outputs.
- Both can be used together: monitoring for broad coverage, and a control plane for enforcing approval gates in specific workflows.
In cosa eccelle Fiddler
Riconosciamo i punti di forza dello strumento, distinguendoli dai deliverable di audit.
- Unified AI observability positioning (monitoring, evaluation, safety/guardrails framing).
- Strong fit when the program starts with model/agent monitoring, reporting, and guardrail signals.
Dove i team regolamentati hanno ancora bisogno di un livello aggiuntivo
- Decision-time workflow governance: who can approve/override/stop an agent action, and how that gate is enforced.
- Policy checkpoints embedded in the workflow that can block/review/allow actions (with evidence of enforcement).
- Deliverable-shaped evidence exports (Annex IV mapping + oversight records + manifest + checksums), not only monitoring dashboards.
Pronto all'uso vs da costruire
Una suddivisione equa tra ciò che è disponibile come workflow principale e ciò che va assemblato tra più sistemi.
Pronto all'uso
- Monitoring and reporting across AI systems (quality, safety, and risk signals).
- Guardrail and evaluation framing for responsible AI programs.
- Dashboards/alerts for continuous monitoring and incident response workflows.
Possibile, ma lo costruite voi
- A decision-time gate that blocks high-risk workflow actions until approved (with escalation and override rules).
- Workflow decision records (approvals/overrides) tied to business actions, not just model outputs.
- A packaged evidence bundle export mapped to Annex IV/oversight deliverables, with verification artifacts.
- Retention and integrity controls for long-lived audit records.
Esempio concreto di workflow regolamentato
Uno scenario che mostra dove si colloca ciascun livello.
Credit underwriting recommendation
An agent proposes approve/deny decisions with supporting rationale. Monitoring tells you how the system behaves over time; regulated workflows often also require a decision-time gate before the final decision is issued.
Dove Fiddler è utile
- Monitor drift, performance regressions, and guardrail outcomes across models and cohorts.
- Trigger investigations when risk signals breach thresholds.
Dove KLA è utile
- Enforce an approval checkpoint before a high-impact decision is issued or acted on.
- Capture who approved/overrode the recommendation (and what they saw) as an auditable decision record.
- Export a verifiable evidence pack for reviewers and auditors (manifest + checksums).
Decisione rapida
Quando scegliere l'uno o l'altro (e quando acquistare entrambi).
Scegliete Fiddler quando
- Your primary requirement is broad AI monitoring and reporting across many models.
- You are building a measurement program first and governance controls later.
Scegliete KLA quando
- You need to govern workflow actions (not only monitor models) with approvals and policy gates.
- You need evidence packs with integrity verification for audits.
Quando non acquistare KLA
- You only need monitoring dashboards and alerts and don’t require approval queues or evidence exports.
Se acquistate entrambi
- Use Fiddler to understand performance and risk signals.
- Use KLA to enforce controls at decision time and export the evidence pack auditors ask for.
Cosa KLA non fa
- KLA is not designed to replace broad AI monitoring platforms for organization-wide reporting.
- KLA is not a request gateway/proxy for model access.
- KLA is not a prompt experimentation suite.
Il ciclo di controllo di KLA (Governare / Misurare / Dimostrare)
Cosa significa "evidenze di livello audit" in termini di funzionalità di prodotto.
Governare
- Checkpoint policy-as-code che bloccano o richiedono revisione per le azioni ad alto rischio.
- Code di approvazione basate sui ruoli, escalation e override registrati come record decisionali.
Misurare
- Revisioni a campione basate sul rischio (baseline + intensificate durante incidenti o dopo modifiche).
- Tracciamento dei near-miss (passaggi bloccati o quasi bloccati) come segnale di controllo misurabile.
Dimostrare
- Traccia di audit tamper-proof, append-only, con timestamping esterno e verifica di integrità.
- Bundle di esportazione dall'Evidence Room (manifesto + checksum) verificabili in modo indipendente dagli auditor.
Nota: alcuni controlli (SSO, workflow di revisione, finestre di conservazione) dipendono dal piano. Consultate /pricing?ref=confronto.
Checklist RFP (scaricabile)
Un artefatto di procurement condivisibile.
# Checklist RFP: KLA vs Fiddler Utilizzate questa checklist per valutare se gli strumenti di "osservabilità / gateway / governance" coprono effettivamente i deliverable di audit per workflow regolamentati basati su agenti. ## Requisiti essenziali (deliverable di audit) - Mappatura delle esportazioni in stile Annex IV (campi della documentazione tecnica -> evidenze) - Registri di supervisione umana (code di approvazione, escalation, override) - Piano di monitoraggio post-market + sampling policy basata sul rischio - Traccia di audit tamper-evident (verifiche di integrità + conservazione a lungo termine) ## Chiedete a Fiddler (e al vostro team) - Can you enforce decision-time controls (block/review/allow) for high-risk actions in production? - How do you distinguish “human annotation” from “human approval” for business actions? - Can you export a self-contained evidence bundle (manifest + checksums), not just raw logs/traces? - What is the retention posture (e.g., 7+ years) and how can an auditor verify integrity independently? - How do you connect monitoring signals to enforceable workflow gates and a packaged evidence export for audits?
Fonti
Riferimenti pubblici utilizzati per mantenere questa pagina accurata e imparziale.
Nota: le funzionalità dei prodotti cambiano. Se notate informazioni obsolete, segnalatelo tramite /contact?ref=confronto.